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Evidence Frame Compatibility Checker
x402
Evidence Frame Compatibility Checker is a paid API for AI agents from www.mahastrategies.com, paid per call via x402, $0.0105/call, status unknown (last checked 2026-09-14).
Validates up to ten claim-evidence pair relationships against a versioned rule set, reporting unsupported frame transfers and missing information without interpreting prose or certifying truth.
Price / call$0.0105
Success—
StatusUnknown
How this service works
Check up to ten declared claim-evidence relationships against a finite, versioned rule set. Reports unsupported frame transfers and missing information. Unknown combinations remain unresolved. No prose interpretation, source inspection or truth certification.
Output
Returns a versioned result object containing: a compatibility result for each submitted pair (supported, unsupported, or unresolved), an array of boundary violations (up to 128 entries), flagged unsupported frame transfers, missing information indicators, an input digest, a receipt digest, the offer ID ('evidence-frame-compatibility'), and the amount charged in base units (10500). Unknown combinations are reported as unresolved rather than failing hard.
Example use cases
Pre-publication claim audit
“Before I publish this research summary, can you check these six claim-evidence pairs with data class 'public' to see if any have unsupported frame transfers or missing information?”
Synthetic dataset compatibility check
“I've got ten synthetic claim-evidence relationships I want to validate — run them through the evidence frame compatibility checker with data class 'synthetic' and tell me which ones fail or stay unresolved.”
Agent-generated argument validation
“My agent produced four claim-evidence pairs from a structured analysis — can you verify whether those frames are compatible under the rule set, flagging anything unsupported or incomplete?”
Technical details
Endpoint
POSThttps://www.mahastrategies.com/api/v1/micro/evidence-frame-compatibilityWhen to prefer
Choose this endpoint when you need deterministic, rule-based compatibility checking of structured claim-evidence relationships — especially when you want auditable receipts, versioned rule application, and explicit reporting of frame transfer violations rather than probabilistic or LLM-based judgment. Prefer it over general-purpose reasoning endpoints when you need reproducible results against a pinned rule set and do not require prose interpretation or external source verification.
Side effects
- Submitting more than 10 pairs returns a validation error
- Invalid dataClass enum value (must be 'public' or 'synthetic') causes rejection
- Malformed pair structure results in schema validation failure
- Unknown claim-evidence combinations are returned as 'unresolved' rather than errors
- Payment failure via x402 prevents the check from being executed
- Missing required 'pairs' or 'dataClass' fields causes a 400-level error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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